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Healthcare AI to Play Major Role in $15.7 Trillion Economic Boost

Artificial intelligence in healthcare is expected to play a significant role in bringing a $15.7 trillion boost to the global economy.

February 28, 2019 - Advances in artificial intelligence within the healthcare industry will contribute significantly to the $15.7 trillion economic boost related to machine learning, according to a new report from PwC.

The firm anticipates a 14.5 percent increase in North America’s GDP by 2030, driven largely by AI’s ability to reduce waste, and support better decision-making.

Gains in productivity are expected to contribute $6.6 trillion to the overall total.

“From the personal assistants in our mobile phones, to the profiling, customization, and cyber protection that lie behind more and more of our commercial interactions, AI touches almost every aspect of our lives. And it’s only just getting started,” the report said.

“AI is set to be the key source of transformation, disruption and competitive advantage in today’s fast changing economy.”

Every part of healthcare is lining up for change: providers, pharma and life sciences, payers, and consumers should all prepare for deeper integration of artificial intelligence into their processes and experiences.

“AI-powered diagnostics use the patient’s unique history as a baseline against which small deviations flag a possible health condition in need of further investigation and treatment,” the report explains.

“AI is initially likely to be adopted as an aid, rather than replacement, for human physicians. It will augment physicians’ diagnoses, but in the process also provide valuable insights for the AI to learn continuously and improve.”

Despite the huge potential, however, healthcare is likely to see slower adoption than many other industries.

Sectors such as retail, logistics, and financial services may have more immediately obvious opportunities for automation, and are more likely than healthcare to see widespread adoption within the next one to three years.

While 54 percent of retail organizations are expected to reach AI maturity by 2022, just 37 percent of healthcare entities are likely to do the same.

The financial services sector is anticipated to be fully AI-driven within the next seven years, but 40 percent of healthcare stakeholders will still need to work on infusing artificial intelligence into their operations during that time period.

Healthcare faces different challenges than these other industries, including strict privacy and security regulations and a deeply-rooted legacy technology environment, both of which make it difficult for organizations to apply machine learning techniques to their data assets.

In addition, healthcare organizations tend to face pushback from employees when introducing changes to workflows, especially when those changes raise the fear of job loss or alterations to the patient-provider relationship.

All of these issues have combined to produce skepticism around AI in healthcare that has limited and slowed adoption.

In 2017, more than a third of organizations responding to a HIMSS Analytics survey said they are planning to wait until AI is much more mature before implementing machine learning tools into their organizations.

A quarter added that they could not see a clear business case for AI, and 19 percent stated that the opportunities for machine learning were hard to understand.

Artificial intelligence has advanced significantly since that time, even though only two years have passed. However, PwC still sees the same barriers and challenges in the current environment.

In order to bring AI into healthcare at scale, “it would be necessary to address concerns over the privacy and protection of sensitive health data,” the report states.

“The complexity of human biology and the need for further technological development also mean than some of the more advanced applications may take time to reach their potential and gain acceptance from patients, healthcare providers and regulators.”

Clinical staff will need to be introduced to AI-driven clinical decision support slowly and carefully in order to overcome resistance and encourage adoption, PwC suggested.

“Continuous interaction between human physicians and the AI-powered diagnostics will enhance the accuracy of the systems and, over time, provide enough confidence for humans to delegate the task entirely to the AI system to operate autonomously,” the report said.

“Faster and more accurate diagnoses and more personalized treatment in the short and medium-term, which would pave the way for longer-term breakthroughs in areas such as intelligent implants.”

In the short term, however, there are numerous opportunities to automate administrative tasks and financial transactions, the brief added.

The insurance side of the industry may be particularly ripe for near-term disruption, since automated scheduling and claims processing are likely to face far less resistance than patient-facing tasks.

Provider organizations also appear more willing to delegate non-clinical tasks to artificial intelligence, and are currently exploring opportunities to improve patient experiences through virtual assistants, AI applications, and other consumer-friendly tools.

Leveraging artificial intelligence to improve EHR workflows is another area of promise that is already bearing fruit. The majority of large health IT vendors are quickly integrating machine learning into their technology offerings in order to streamline administrative processes and reduce frustration among end-users.

Using non-clinical avenues to introduce AI into the healthcare environment may be the optimal approach for healthcare organizations facing wariness from clinicians but still interested in staying on the cutting edge of technology.

“Doing nothing is not a feasible option,” cautioned PwC. “It’s easy to dismiss a lot of what’s said about AI as hype. Yet as our analysis underlines, without decisive response, many well established enterprises and even whole business models are at risk of being rendered obsolete.”

PwC advises organizations to assess themselves for vulnerabilities to disruption, identify opportunities to proactively embrace AI, and start quickly building up talent to incorporate AI into the organization.

“Get this right and creativity, collaboration and decision making within your organization can all be empowered. You’ll have the potential to understand customer behavior and anticipate and respond to their individual needs with a precision and foresight that have never been possible before.”

“As a business leader, you may therefore have to take a leap of faith,” the report concluded. “The prize is being far more capable, in a far more relevant way, than your business could ever be without the infinite possibilities of AI.”